Help files call attributes() a function. Its syntax looks like a function call. Even class(attributes) calls it a function.
But I see I can assign something to attributes(myobject), which seems unusual. For example, I cannot assign anything to log(myobject).
So what is the proper name for "functions" like attributes()? Are there any other examples of it? How do you tell them apart from regular functions? (Other than trying supposedfunction(x)<-0, that is.)
Finally, I guess attributes() implementation overrides the assignment operator, in order to become a destination for assignments. Am I right? Is there any usable guide on how to do it?
Very good observation Indeed. It's an example of replacement function, if you see closely and type apropos('attributes') in your R console, It will return
"attributes"
"attributes<-"
along with other outputs.
So, basically the place where you are able to assign on the left sign of assignment operator, you are not calling attributes, you are actually calling attributes<- , There are many functions in R like that for example: names(), colnames(), length() etc. In your example log doesn't have any replacement counterpart hence it doesn't work the way you anticipated.
Definiton(from advanced R book link given below):
Replacement functions act like they modify their arguments in place,
and have the special name xxx<-. They typically have two arguments (x
and value), although they can have more, and they must return the
modified object
If you want to see the list of these functions you can do :
apropos('<-$') and you can check out similar functions, which has similar kind of properties.
You can read about it here and here
I am hopeful that this solves your problem.
Related
I'm working in R, and I'd like to define some variables that I (or one of my collaborators) cannot change. In C++ I'd do this:
const std::string path( "/projects/current" );
How do I do this in the R programming language?
Edit for clarity: I know that I can define strings like this in R:
path = "/projects/current"
What I really want is a language construct that guarantees that nobody can ever change the value associated with the variable named "path."
Edit to respond to comments:
It's technically true that const is a compile-time guarantee, but it would be valid in my mind that the R interpreter would throw stop execution with an error message. For example, look what happens when you try to assign values to a numeric constant:
> 7 = 3
Error in 7 = 3 : invalid (do_set) left-hand side to assignment
So what I really want is a language feature that allows you to assign values once and only once, and there should be some kind of error when you try to assign a new value to a variabled declared as const. I don't care if the error occurs at run-time, especially if there's no compilation phase. This might not technically be const by the Wikipedia definition, but it's very close. It also looks like this is not possible in the R programming language.
See lockBinding:
a <- 1
lockBinding("a", globalenv())
a <- 2
Error: cannot change value of locked binding for 'a'
Since you are planning to distribute your code to others, you could (should?) consider to create a package. Create within that package a NAMESPACE. There you can define variables that will have a constant value. At least to the functions that your package uses. Have a look at Tierney (2003) Name Space Management for R
I'm pretty sure that this isn't possible in R. If you're worried about accidentally re-writing the value then the easiest thing to do would be to put all of your constants into a list structure then you know when you're using those values. Something like:
my.consts<-list(pi=3.14159,e=2.718,c=3e8)
Then when you need to access them you have an aide memoir to know what not to do and also it pushes them out of your normal namespace.
Another place to ask would be R development mailing list. Hope this helps.
(Edited for new idea:) The bindenv functions provide an
experimental interface for adjustments to environments and bindings within environments. They allow for locking environments as well as individual bindings, and for linking a variable to a function.
This seems like the sort of thing that could give a false sense of security (like a const pointer to a non-const variable) but it might help.
(Edited for focus:) const is a compile-time guarantee, not a lock-down on bits in memory. Since R doesn't have a compile phase where it looks at all the code at once (it is built for interactive use), there's no way to check that future instructions won't violate any guarantee. If there's a right way to do this, the folks at the R-help list will know. My suggested workaround: fake your own compilation. Write a script to preprocess your R code that will manually substitute the corresponding literal for each appearance of your "constant" variables.
(Original:) What benefit are you hoping to get from having a variable that acts like a C "const"?
Since R has exclusively call-by-value semantics (unless you do some munging with environments), there isn't any reason to worry about clobbering your variables by calling functions on them. Adopting some sort of naming conventions or using some OOP structure is probably the right solution if you're worried about you and your collaborators accidentally using variables with the same names.
The feature you're looking for may exist, but I doubt it given the origin of R as a interactive environment where you'd want to be able to undo your actions.
R doesn't have a language constant feature. The list idea above is good; I personally use a naming convention like ALL_CAPS.
I took the answer below from this website
The simplest sort of R expression is just a constant value, typically a numeric value (a number) or a character value (a piece of text). For example, if we need to specify a number of seconds corresponding to 10 minutes, we specify a number.
> 600
[1] 600
If we need to specify the name of a file that we want to read data from, we specify the name as a character value. Character values must be surrounded by either double-quotes or single-quotes.
> "http://www.census.gov/ipc/www/popclockworld.html"
[1] "http://www.census.gov/ipc/www/popclockworld.html"
I am using magrittr, and was able to pass one variable to an R function via pipes from magrittr, and also pick which parameter to place where in the situation of multivariable function : F(x,y,z,...)
But i want to pass 2 parameters at the same time.
For example, i will using Select function from dplyr and pass in tableName and ColumnName:
I thought i could do it like this:
tableName %>% ColumnName %>% select(.,.)
But this did not work.
Hope someone can help me on this.
EDIT :
Some below are saying that this is a duplicate of a link provided by others.
But based on the algebra structure of the magrittr definition of Pipe for multivariable functions, it should be "doable" just based on the algebra definition of the pipe function.
The link provided by others, goes beyond the base definition and employs other external functions and or libraries to try to achieve passing multiple parameter to the function.
I am looking for a solution, IF POSSIBLE, just using the magrittr library and other base operations.
So this is the restriction that is placed on this problem.
In most of my university courses in math and computer science we were restricted to use only those things taught in the course. So when I said I am using dplyr and magrittr, that should imply that those are the only things one is permitted to use, so its under this constraint.
Hope this clarifies the scope of possible solutions here.
And if it's not possible to do this via just these libraries I want someone to tell me that it cannot be done.
I think you need a little more detail about exactly what you want, but as I understand the problem, I think one solution might be:
list(x = tableName, y = "ColumnName") %>% {select(eval(.$x),.$y) }
This is just a modification of the code linked in the chat. The issue with other implementations is that the first and second inputs to select() must be of specific (and different) types. So just plugging in two strings or two objects won't work.
In the same spirit, you can also use either:
list(x = "tableName", y = "ColumnName") %>% { select(get(.$x),.$y) }
or
list(tableName, "ColumnName") %>% do.call("select", .).
Note, however, that all of these functions (i.e., get(), eval(), and do.call()) have an environment specification in them and could result in errors if improperly specified. They work just fine in these examples because everything is happening in the global environment, but that might change if they were, e.g., called in a function.
I am still not very good at using R’s standard debugging tools, and I often find that neither the error nor the traceback tell me enough to figure out what is going on. I would like to change R’s default behavior on error to provide more information.
Specifically, I would always like the call, including the formals, the expression assigned to each formal (the default expression if the default is the expression assigned), and the value of each of the argument expressions as evaluated in place, all returned in a format that makes it unambiguous which expression has been matched to which formal and which values go with which expression. Since the values might be large or of unexpected or evanescent type, I’d like them to be returned in a format, such as a str(), that makes intelligent choices about truncation and correctly identifies promises and other object types that tend to evaluate themselves into something else before you see them.
And finally, I’d like all these things, together with the return value of each call, for every function on the call stack from the error back to (and including) some piece of code that I wrote. It seems to me that the natural structure would be a single R object, a list of lists, one list per call (perhaps tidied, broom-like, into a tibble with some list columns) that I could single-step through in the obvious way.
I apologize if I have described some standard R debugging tool that I just haven't learned how to use properly yet. Is this even possible? If it is, could it be implemented via R's available error handlers, or would it need some package-scale coding project?
I would most prefer a solution that changes the default error response to this, but if that is impracticable, I'd accept a solution that requires that I rerun a code chunk with a wrapper or something similar.
I come from a C# background and try to migrate some of my time series library to R.
One of the benefits of OOP is that I can tuck away variables in a class and pass this as reference.
I read up on R environments, lists, ... and I'm still not sure about the right approach. If I would use a list then I would need to check the function argument:
exists()
(btw: Is there also a function to test for the elements in a list)
I could create a list, pass it as an argument and then write the result back in a list. But is this the right approach?
Any comments ...
exists is seldom used. If you need it, maybe you do something wrong.
missing is sometimes used.
Functions sometimes, but not very often, receive lists as parameters, and often return lists.
To test whether a list foo has an element bar, use is.null(foo$bar). This is FALSE if the list has the element, TRUE otherwise.
I was going through some examples in hadley's guide to functionals, and came across an unexpected problem.
Suppose I have a list of model objects,
x=1:3;y=3:1; bah <- list(lm(x~y),lm(y~x))
and want to extract something from each (as suggested in hadley's question about a list called "trials"). I was expecting one of these to work:
lapply(bah,`$`,i='call') # or...
lapply(bah,`$`,call)
However, these return nulls. It seems like I'm not misusing the $ function, as these things work:
`$`(bah[[1]],i='call')
`$`(bah[[1]],call)
Anyway, I'm just doing this as an exercise and am curious where my mistake is. I know I could use an anonymous function, but think there must be a way to use syntax similar to my initial non-solution. I've looked through the places $ is mentioned in ?Extract, but didn't see any obvious explanation.
I just realized that this works:
lapply(bah,`[[`,i='call')
and this
lapply(bah,function(x)`$`(x,call))
Maybe this just comes down to some lapply voodoo that demands anonymous functions where none should be needed? I feel like I've heard that somewhere on SO before.
This is documented in ?lapply, in the "Note" section (emphasis mine):
For historical reasons, the calls created by lapply are unevaluated,
and code has been written (e.g. bquote) that relies on this. This
means that the recorded call is always of the form FUN(X[[0L]],
...), with 0L replaced by the current integer index. This is not
normally a problem, but it can be if FUN uses sys.call or
match.call or if it is a primitive function that makes use of the
call. This means that it is often safer to call primitive functions
with a wrapper, so that e.g. lapply(ll, function(x) is.numeric(x))
is required in R 2.7.1 to ensure that method dispatch for is.numeric
occurs correctly.